Google's AI can accurately predict floods 7 days in advance
Google has made significant strides in the use of artificial intelligence (AI) to forecast river floods up to a week before they occur. The results, shared in the scientific journal Nature, underscore a major advancement as floods are the most frequent natural disaster globally, affecting nearly 1.5 billion people. Google's AI has overcome prediction hurdles by harnessing diverse data sets, such as past incidents and topographical readings.
How Google's AI provides accurate flood prediction
Google's AI has triumphed in predicting floods by training machine learning models using an array of data, encompassing past occurrences, river gauge readings, altitude, and landscape information. The tech giant created detailed maps and executed hundreds of thousands of simulations for each area. This exhaustive method allowed the models to accurately forecast imminent floods, even in areas with sparse data. The technology was especially beneficial in underrepresented regions like Africa and Asia where conventional flood prediction has been problematic.
Google's AI flood forecasts benefit 460 million people
Google's AI-driven flood forecasts have been made available to 460 million people across 80 countries. The company has incorporated these predictions into various platforms such as Google Search, Google Maps, and Android, along with its exclusive Flood Hub web application which commenced operations in 2022. This extensive reach has significantly enhanced the dependability of global flood forecasts, extending the average prediction period from zero to five days.
Google's future endeavors for AI flood forecasting
Google intends to further delve into the potential of machine learning to develop superior flood forecasting models. The company has joined forces with academic researchers to refine its AI-centric approach. This partnership aims to create a comprehensive global flood forecasting platform that harnesses the power of AI to predict one of the most frequent natural disasters more accurately and efficiently.
